# ------------- file paths --------------------------------------------------

SUBSCRIBER_PATH = '../../data/grouped_subs.csv'
MARKET_PATH = '../../data/grps.csv'

CHIS_PATH = '../../data/orig/CHIS'
CHRONIC_CONDITION_PATH = '../../data/orig/ChronicConditionsMed'
CENSUS_PATH = '../../data/orig/UninsuredRateByRAYearandAge.txt'

# ------------- categorical variable cuts -----------------------------------

VAR_AGE = 'age_bins'
VAR_INC = 'fpl_bins'
VAR_ACG = 'acg_quartiles'

CUTS_AGE = 'cuts_age.pickle' # age
CUTS_INC = 'cuts_inc.pickle' # income
CUTS_ACG = 'cuts_acg.pickle' # ACG score

# ------------- parameters --------------------------------------------------

# Set which variables to condition on. Should include year and age, and can
# include one of metro/urban to capture MSAs or Claritas scores respectively.
# Metro --> RA in oregon calculations (using conditionals2).
conditionals = ['year', 'age', 'metro']
conditionals2 = ['year', 'age', 'ra']

# Set which other demographic variables to include. Should include income,
# and can include is_married and/or has_children.
demographics = ['income', 'is_married', 'has_children', 'acg_quartiles']

# set the order by which to impute missing group uninsurance rates
unins_impute_order = ['year', 'metro', 'age'] + demographics

# Define which Rating Areas are urban/metropolitan. Maybe 4 too?
# Cf. RA map and MSA map
urban_ras = [1, 2, 3, 7]

# ------------- options -----------------------------------------------------

# turn summary stats on/off
SUMSTATS = 1

def display(*s):
    if SUMSTATS == 1:
        print(*s)